For expository convenience, the present invention will be illustrated with reference to one particular application thereof, namely as a frequency estimator in a spectrum analyzer However, it should be recognized that the invention is not so limited.
Spectrum analyzers typically operate by mixing a signal of interest with one or more local oscillator signals to produce an intermediate frequency (IF) signal. This signal is then processed to categorize its spectral components in a spectrum of interest and the results displayed on a screen for viewing. The screen typically displays 400 data points, each representing the spectral content of the signal in one of 400 contiguous sub-bands that together span the spectrum of interest.
It is often desirable to measure the frequency of a particular spectral component. The limited screen resolution, however, makes such measurement difficult. For example, if the instrument is analyzing a signal's spectral components in the range of 10 to 20 MHz, each of the 400 sub-bands (or "bins" as they are often called) represents 25 KHz of the spectrum. Thus, it is impossible to discern from the display the frequency of a particular frequency component to an accuracy better than 25 KHz.
In the prior art, some attempts have been made to better resolve the frequency of signal components in spectrum analyzers. These attempts have principally involved counting zero crossings of the instrument's IF signal over a fixed period of time and deducing from such number of crossings the frequency of the signal. Such approaches, however, require extended periods of time to obtain accurate results and further require hardware not normally included in the instrument.
To more quickly and simply provide an accurate frequency estimate, the present invention monitors the phase of the IF waveform at a plurality of periodically spaced sample points. These phase samples are "unwrapped" to provide cumulative phase totals at each sampled point of the waveform. The phase rate of change is then determined by linear regression techniques. Since the phase rate of change is the signal frequency, the result of the linear regression analysis yields the IF frequency. The frequency of the input signal waveform can then be determined since the frequencies of the local oscillators with which the input signal waveform was mixed are known .